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Workshop B4. The Collection and Processing of Survey Data Using Mobile Technologies

Workshop B4. The Collection and Processing of Survey Data Using Mobile Technologies. Workshop Participants. Notes: Sizable group (n=28) High attendance and participation rates No incentives offered.

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Workshop B4. The Collection and Processing of Survey Data Using Mobile Technologies

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  1. Workshop B4. The Collection and Processing of Survey Data Using Mobile Technologies

  2. Workshop Participants • Notes: • Sizable group (n=28) • High attendance and participation rates • No incentives offered Workshop Chair: Jean Wolf, United StatesResource Paper Author: Peter Stopher, AustraliaDiscussant: Barbara Noble, United Kingdom Rapporteur: Sean Doherty, Canada Contributing Authors Stephan Krygsman, South Africa Maat Kees,The Netherlands Nadine Schüssler, Switzerland Other Participants

  3. Workshop Scope • Really did focus on data collection and processing using mobile technologies • Tried to stay away from non-response • Limited discussion on broader study design

  4. State of the Art - Devices & Data Collection • Device evolution is heading to wearables, but vehicle-based studies may still have a role • Most studies include GPS and diary, but trend towards GPS only • Interview and delivery deployment methods vary • Viable alternatives to GPS are being evaluated • Mobile/cell phone options (now) Also used for CAPI • Bluetooth / WiFi / RFID / smartcard / RDS (in research) • Alternatives have different levels of detail, precision, cost, coverage • Mixed modes (tech and non-tech) could be used • Select methods and solution(s) based on purpose / need

  5. State of the Art – Data Processing • Various algorithms developed to identify key diary elements • stops, trips – OD / route / distance / start time / duration • travel mode • trip purpose • Use of GIS datasets important (road network, transit network, points of interest, land use, etc.) • Still largely in exploratory phase • Some implementing rule based, others using fuzzy logic • Little validation and little ‘ground truth’ to do it • Prompted recall interfaces developed and implemented, but burden is an issue • Mobile/cell phone research showing promise

  6. Issues - Devices and Data Collection • Deploying/retaining devices • On/off switch desirable ? • Logging rules (e.g., frequency, speed screen) • Missing data / messy data • Age cut off for deployment (practicality and ethics) • Reducing bias • Encryption/security • Ethics • Avoiding lawsuits • Retaining/archiving raw data • Cost of cell-based location for large samples • Practicality of large scale location-enabled mobile phones (commercial considerations) • How best to recruit and communicate with subjects

  7. Issues - Data Processing • Lack of available software – commercial, share/free ware • Are we ready to standardize? • Data Collection (NMEA parsing) • Data Storage (XML desirable) • Algorithms • Calibration/validation data essential, but challenging to acquire • Prompted recall offers some potential • Direct observation may be needed • Assessing respondent burden from prompted recall • Different methods used, e.g., fuzzy logic, AI, rule-based,…

  8. Research Needs – Data Collection • Continued improvements in mobile technology devices • Functionality, cost, power capacity, storage capacity, etc. • Deployment method analyses with respect to study purpose, cost, response rates • Continued research on mobile phone ‘tower location’ traces for travel surveys • Feasibility study for deployment of custom software for population-based mobile phone user sample • Possible joint venture research – government, private, university (e.g., health or tourism research) • How young should or could participants be? • Impact of Galileo on accuracy and coverage?

  9. Research Needs – Data Processing • Standard data, standard processing software, or perhaps algorithm modules • Commercial or free processing software (are we ready?) • Comparative analysis of accuracy of mode and purpose identification • Development of travel companion (who) / party size estimators (and is this really needed?) • Development of validation datasets • Development of algorithms / software independent of GIS • Overall methodology (GPS/CATI, GPS/PR, GPS only) tradeoff analysis (burden, quality, bias, cost). Same for mobile phones. • Pushing the modelling paradigms (e.g., number of travel days, number of persons per household, data elements, travel time measurements)

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